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A Design of Effective Inference Methods and Their Application Guidelines for Supporting Various Medical Analytics Schemes

다양한 의료 분석 방식을 지원하는 효과적 추론 기법 설계 및 적용 지침

  • Received : 2015.07.29
  • Accepted : 2015.09.14
  • Published : 2015.12.15

Abstract

As a variety of personal medical devices appear, it is possible to acquire a large number of diverse medical contexts from the devices. There have been efforts to analyze the medical contexts via software applications. In this paper, we propose a generic model of medical analytics schemes that are used by medical experts, identify inference methods for realizing each medical analytics scheme, and present guidelines for applying the inference methods to the medical analytics schemes. Additionally, we develop a PoC inference system and analyze real medical contexts to diagnose relevant diseases so that we can validate the feasibility and effectiveness of the proposed medical analytics schemes and guidelines of applying inference methods.

다양한 개인 의료 장비들이 등장함에 따라 개인 의료 컨텍스트가 풍부하게 수집되고 있다. 이렇게 수집된 의료 컨텍스트를 분석함으로써 소프트웨어적으로 질병을 진단하기 위한 노력이 이어지고 있다. 본 논문에서는 의료 전문가들이 사용하는 의료 분석 기법을 정형화하고, 각 의료 기법을 실현화하기 위한 추론 기법을 식별하며, 추론기법의 적용 지침을 제시한다. 또한, 의료 기법을 제공하는 추론 시스템을 PoC 수준에서 개발하고, 실제 의료 컨텍스트를 분석하여 질병 진단 실험을 수행함으로써 제시하는 의료 분석 기법 및 추론 기법 적용 지침의 실효성과 그 효과를 검증한다.

Keywords

Acknowledgement

Supported by : 한국연구재단

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